Features

Powerful Performance

P3 instances allow you to build and deploy advanced applications with up to 14 times better performance than previous-generation Amazon EC2 GPU compute instances. With up to 8 NVIDIA Tesla V100 GPUs, P3 instances provide up to one petaflop of mixed-precision, 125 teraflops of single-precision, and 62 teraflops of double-precision floating point performance. P3 instances also feature up to 64 vCPUs based on custom Intel Xeon E5 (Broadwell) processors and 488 GB of DRAM.

Scalability

For P3 instances with multiple GPUs, a 300 GB/s next-generation NVIDIA NVLink interconnect enables high-speed, low-latency GPU-to-GPU communication. This combined with Amazon EC2 ENA-based Enhanced Networking that support up to 25 Gbps network bandwidth, applications can benefit from multiple GPUs to scale-up and scale-out as needed. P3 instances are well-suited for distributed deep learning frameworks, such as MXNet, that scale out with near perfect efficiency.

Product Details

Instance Size

GPUs - Tesla V100

GPU Peer to Peer

GPU Memory (GB)

vCPUs

Memory (GB)

Network Bandwidth

EBS Bandwidth

p3.2xlarge

1

N/A

16

8

61

Up to 10Gbps

1.5Gbps

p3.8xlarge

4

NVLink

64

32

244

10Gbps

7Gbps

p3.16xlarge

8

NVLink

128

64

488

25Gbps

14Gbps

Benefits

Speed

Whether it’s machine learning (training, inference), HPC workloads, or any other floating point sensitive workload, you will realize tremendous gains in processing time and throughput by using the cutting-edge performance of the NVIDIA Tesla V100 GPUs.

Agility

With P3 instances, you can take full advantage of hyper-scale cloud infrastructure to deploy GPU resources in a matter of minutes. Coupled with a pay-as-you-go usage model and AWS’s rapid pace of innovation, engineering teams can bring new innovations to market faster, while optimizing their total operational costs.

Get started with P3 instances

To get started within minutes, use the Amazon Deep Learning AMI, pre-installed with popular deep learning frameworks such as Caffe2 and Mxnet. Alternatively, you can also use the NVIDIA AMI with GPU driver and CUDA toolkit pre-installed.